My Digital Apprenticeship with Bristol Museums so far

My name is Caroline James and I am currently in my fourth week of my Digital Marketing Apprenticeship with Bristol Museums.

I am originally from Luton and moved to the South West in 2013 when I was 18 years old to do my degree in Diagnostic Radiography, at the University of Exeter. I loved the south west so much I didn’t want to leave! So once I finished my degree and became a qualified radiographer, I moved to Bristol in 2016 and worked at Southmead Hospital. Although I absolutely loved going to university and had an interesting experience working for the NHS, after being a healthcare worker for three years, I realised it was no longer for me and wanted to have a career change. I wanted to do something more creative and have been interested in digital marketing for a long time.

I thought an apprenticeship was a good route for me as I wanted to learn new skills and use them in a real life setting. So I went on the government website and found this apprenticeship at the museum, and thought it looked great! 

I feel extremely privileged to have got this apprenticeship and I am already learning so much. I loved visiting Bristol Museum and Art Gallery and M Shed even before I moved to Bristol, so it is incredibly fulfilling to be doing digital marketing for institutions I really care about. 

So far I have helped with the launch of a project entitled “Uncomfortable Truths”. This is where a group of BAME students and alumni came together to create podcasts where they discussed their interpretation of certain objects within the museum that have an uncomfortable and controversial side to them – this includes how they were collected and what they represent.

I helped with creating a webpage presenting the project, the podcasts and its creators using WordPress. I helped upload the podcasts onto Soundcloud, and then took the WordPress code generated for each podcast and uploaded it to the webpage. I also assisted with the design of an information leaflet for the launch using a website called Canva.  

The launch itself went incredibly well and it was very interesting. I hope more podcasts discussing the complex cultural and colonial histories behind objects within the museum are created.

Additionally, I’ve been helping with the social media campaigns for the museum shop products using Hootsuite. I look forward to updating the blogs on the museum website and producing email newsletters in the near future. 

Furthermore, I get to help with the creation and the promotion of the “Stories” on the Bristol Museums website, which go in depth about black history in Bristol. 

I expect there will be many more projects and assignments that I will get to be a part of as a member of the Digital Team that will assist with my understanding of digital marketing. Furthermore, I am incredibly excited about the qualification I will be gaining from this apprenticeship and look forward to learning about the fundamentals of digital marketing such as Google Analytics and SEO. It has only been a few weeks but I am already realising what an amazing place it is to work with many teams of incredibly skilled people working together. There are so many opportunities to learn and I cannot wait to gain more skills over the next two years.



SENSORS IN MUSEUMS

ZENGENTI HACK DAY

Background

One of our digital team objectives for this year is to do more with data, to collect, share and use it in order to better understand our audiences, their behaviour and their needs. Online, Google analytics provides us with a huge amount of information on our website visitors, and we are only just beginning to scratch the surface of this powerful tool.  But for physical visitors, once they come through our doors their behaviour in our buildings largely remains a mystery. We have automatic people counters that tell us the volume of physical visits, but we don’t know how many of these visitors make their way up to the top floor, how long they stay, and how they spend their time. On a basic level, we would like to know which of our temporary exhibitions on the upper floors drive most traffic, but what further insight could we get from more data? 

We provide self complete visitor surveys via ipads in the front hall of our museums, and we can manually watch and record behaviour – but are there opportunities for automated processing and sensors to start collecting this information in a way which we can use and without infringing on people’s privacy? What are the variables that we could monitor?

Hack Time!

We like to collaborate, and welcome the opportunity to work with technical people to try things out, so the invitation to join the yearly “Lockdown” hack day at Zengenti – a 2 day event where staff form teams to work on non-work related problems. This gave us a good chance to try out some potential solutions to in gallery sensors. Armed with Raspberry Pis, webcams, an array of open source tech (and the obligatory beer) the challenge to come up with a system that can glean useful data about museum visitors at a low cost and using fairly standard infrastructure.

Team: 

Atti Munir – Zengenti 

Dan Badham – Zengenti

Joe Collins – Zengenti 

Ant Doyle – Zengenti 

Nic Kilby – Zangenti

Kyle Roberts – Zengenti

Mark Pajak – Bristol Museum

Mission: 

  • Can we build a prototype sensor that can give us useful data on visitor behaviour in our galleries?
  • What are the variables that we would like to know?
  • Can AI automate the processing of data to provide us with useful insights?
  • Given GDPR,what are the privacy considerations? 
  • Is it possible to build a compliant and secure system that provides us with useful data without breaching privacy rights of our visitors?

Face API

The Microsoft Azure Face API is an online “cognitive service” that is capable of detecting and comparing human faces, and returning an image analysis containing data on age, gender, facial features and emotion. This could potentially give us a “happy-o-meter” for an exhibition or something that told us the distribution of ages over time or across different spaces. This sort of information would be useful for evaluating exhibition displays, or when improving how we use internal spaces for the public.

Face detection: finding faces within an image.

Face verification: providing a likeliness that the same face appears in 2 images.

Clearly, there are positive and negative ramifications of this technology as highlighted by Facebook’s use of facial recognition to automatically tag photos, which has raised privacy concerns. The automated one-to-many ‘matching’ of real-time images of people with a curated ‘watchlist’ of facial images is possible with the same technology, but this is not what we are trying to do – we just want anonymised information that can not be related back to any specific person. Whilst hack days are about experimentation and the scope is fairly open to build a rough prototype – we should spend time reviewing how regulations such as GDPR affect this technology because by nature it is a risky area even for purposes of research.

How are museums currently using facial recognition?

  • Cooper Hewitt Smithsonian Design Museum have used it to create artistic installations using computer analysis of the emotional state of visitors to an exhibit.

GDPR and the collecting and processing of personal data

The general data protection regulations focus on the collection of personal data and how it is stored or processed in some way. It defines the various players as data controllers, data processors and data subjects, giving more rights to subjects about how their personal data is used. The concerns and risks around protecting personal data mean more stringent measures need to be taken when storing or processing it, with some categories of data including biometric data considered to be sensitive and so subject to extra scrutiny.

Personal data could be any data that could be used to uniquely identify a person including name, email address, location, ip address etc, but also photographs containing identifiable faces, and therefore video. 

Following GDPR guidelines we have already reviewed how we obtain consent when taking photographs of visitors, either individually or as part of an event. Potentially any system that records or photographs people via webcams will be subject to the same policy – meaning we’d need to get consent – this could cause practical problems for deploying such a system, but the subtleties of precisely how we collect, store and process images are important, particularly when we might be calling upon cloud based services for the image analysis.

In our hypothesised solution, we will be hooking up a webcam to take snapshots of exhibition visitors which will then be presented to the image analysis engine. Since images are considered personal data, we would be classed as data controllers, and anything we do with those images as data processing, even if we are not storing the images locally or in the cloud.

Furthermore – the returned analysis of the images would be classed as biometric data under GDPR and as such we would need explicit consent from visitors to the processing of their images for this specific purpose – non consented biometric processing is not allowed.

We therefore need to be particularly careful in anything we do that might involve images of faces even if we are only converting them to anonymised demographic data without any possibility to trace the data to an individual. The problem also occurs if we want to track the same person across several places – we need to be able to identify the same face in 2 images. 

This means that whilst our project may identify the potential of currently available technology to give us useful data – we can’t deploy it in a live environment without consent. Still – we could run an experimental area in the museum where we ask for consent for visitors to be filmed for research purposes, as part of an exhibition. We’d need to assess whether the benefits of the research outweigh the effort of gaining consent.

This raises the question of where security cameras fall under this jurisdiction….time for a quick diversion: 

CCTV Cameras

As CCTV involves storing images that can be used to identify people, this comes under GDPR’s definition of personal data and as such we are required to have signage in place to inform people that we are using it, and why – the images can only be captured for this limited and specific purpose (before we start thinking we can hack into the CCTV system for some test data)

Live streaming and photography at events

 When we take photographs at events we put up signs saying that we are taking photographs, however whilst UK law allows you to take photos in a public place, passive content may not be acceptable under GDPR when collecting data via image recognition technology.

Gallery interactive displays

Some of our exhibition installations involve live streaming – we installed a cctv camera in front of a greenscreen as part of our Early Man exhibition in order. to superimpose visitors in front of a crowd of prehistoric football supporters from the film. The images are not stored but they are processed on the fly – although it is fairly obvious what the interactive exhibit is doing, should we be asking consent before the visitor approaches the camera, or displaying a privacy notice explaining how we are processing the images?

Background image © Aardman animations

Security

Any solution that involves hooking up webcams to a network or the internet comes with a risk. For the purposes of this hackday we are going to be using raspberry pi connected to a webcam and using this to analyse the images. If this was to be implemented in the museum we’d need to assess the risk of the devices being intercepted .

Authentication and encryption:

Authentication – restrict data to authorised users – user name and password (i.e. consent given)

Encryption  – encoding of the data stream so even if unauthenticated user accesses the stream, they can’t read it without decrypting. E.g. using SSL.

Furthermore –  if we are sending personal data for analysis by a service running online, the geographic location of where this processing takes place is important.

“For GDPR purposes, Microsoft is a data processor for the following Cognitive Services, which align to privacy commitments for other Azure services”

Minimum viable product: Connecting the camera server, the face analyser, the monitoring dashboard and the visualisation. 

Despite the above practical considerations – the team have cracked on with assembling various parts of the solution – using a webcam linked to a Raspberry Pi to send images to the Azure Face API for analysis. Following on form that some nifty tools in data visualisation, and monitoring dashboard software can help users manage a number of devices and aggregate data from them. 

There are some architectural decisions to make around where the various components sit and whether image processing is done locally, on the Pi, or on a virtual server, which could be hosted locally or in the cloud. The low processing power of the Pi could limit our options for local image analysis, but sending the images for remote processing raises privacy considerations.

Step 1: Camera server

After much head scratching we had an application that could be launched on PC or linux that could be accessed over http:// to retrieve a shot from any connected webcam – this is the first part of the puzzle sorted.

By the second day we had a series of webcam devices – raspberry Pi, windows PC stick and various laptops all providing pictures from their webcams via via http requests over wifi – so far so good – next steps are how to analyse these multiple images from multiple devices.

Step 2: Face analyser.

Because the Azure Face API is a chargeable service, we don’t want to waste money by analysing images that don’t contain faces – so we implemented some open source script to first check for any faces. If an image passses the face test – we can then send it for analysis. 

The detailed analysis that is returned in JSON format includes data on age, gender, hair colour and even emotional state of the faces in the picture.

Our first readings are pretty much on point with regards to age when we tested ourselves through our laptop webcams. And seeing the structure of the returned data gives us what we need to start thinking about the potential for visualising this data.

We were intrigued by the faceid code –  does this ID relate to an individual person (which would infer the creation of a GDPR-risky person database somewhere), or simply the face within the image, and if we snapped the same people at different intervals, would they count as different people? It turns out the faceid just relates to the face in an individual image, and does not relate to tracking an individual over time – so this looks good as far as GDPR is concerned, but also limits our ability to deduce how many unique visitors we have in a space if we are taking snaphots at regular intervals.

We had originally envisaged that facial analysis of a series of images from webcams could give us metrics on headcount and dwell time. As the technology we are using requires still images captured from a webcam – we would need to take photos on a regular period to get the figures for a day. 

Taking a closer look at the “emotion” JSON data reveals a range of emotional states, which when aggregated over time could give us some interesting results and raise more questions – are visitors happier on certain days of the week? Or in some galleries? Is it possible to track the emotion of individuals, albeit anonymously, during their museum experience?

In order to answer this we’d need to save these readings in a database with each recorded against a location for the location and time of day – the number of potential variables are creeping up. 

We would also need to do some rigorous testing that the machine readings were reliable – which raises the question about how the Face API is calibrated in the  first place…but as this is just an experiment our priority is connecting the various components – fine tuning of the solution is beyond the scope of this hack.

Step 3: Data exporter 

Prometheus is the software we are using to record data over time and provide a means to query the data and make it available to incoming requests from a monitoring server. We identified the following variables that we would like to track – both to monitor uptime of each unit and also to give us useful metrics.

Essential

  • CPU gauge
  • Memory gauge
  • Disk Space gauge
  • Uptime
    • Uptime (seconds) counter
  • Services
    • Coeus_up (0/1) gauge
    • Exporter_up (0/1) gauge
  • Face count
    • current_faces (count) gauge
    • Face_id (id)
    • Total_faces (count) summary

Nice to have

  • Gender
    • male/female
      1. Gender (0/1) gauge
  • Age
    • Age buckets >18 18<>65 <65 histogram
  • Dwell duration
    • Seconds
      1. Dwell_duration_seconds gauge
  • Services
    • Coeus_up (0/1) gauge
    • Exporter_up (0/1) gauge
  • Coeus
    • API queries 
      1. API_calls (count) gauge
      2. API_request_time (seconds) gauge
  • Exporter
    • Exporter_scrape_duration_seconds gauge

Step 4: Data dashboard

Every data point carries a timestamp and so this data can be plotted along an axis of time and displayed on a dashboard to give a real time overview of the current situation.

Step 5: Data visualisation 

Using D3 we can overlay a graphic representing each face/datapoint back onto the camera feed. In our prototype mock up each face is represented by a shape giving an indication of the ir position within the fame. Upon this we could add colour or icons illustrating any of the available data from the facial analysis.

Tools

Github: Everything we did is openly available on this code repository: https://github.com/blackradley/coeus

Slack: we used this for collaboration during the project – great for chat and sharing documents and links, and breakout threads for specific conversations. This became the hive of the project.

Prometheus: monitoring remote hardware

Grafana: open source dashboard software

Azure: image recognition

Codepen:a  code playground

D3: visualization library

Final remarks

Our aim was to get all the bits of the solution working together into a minimum viable product – to get readings from the webcam into a dashboard. With multiple devices and operating systems there could be many different approaches to this in terms of deployment methods, network considerations and options for where to host the image processing technology. We also wanted a scalable solution that could be deployed to several webcam units.

Just getting the various pieces of the puzzle working would most likely take up the whole time as we sprinted towards our MVP. As we started getting the data back it was starting to become clear that the analysis of the data would present its own problems, not just for reliability, but how to structure it and what the possibilities are – how to glean a useful insight from the almost endless tranches of timestamped data points that the system could potentially generate, and the associated testing, configuring and calibrating that the finished solution would need.

Whilst the Azure Face API will merrily and endlessly convert webcam screenshots of museum visitors to data points – the problem we face is what to make of this. Could this system count individuals over time, and not just within a picture? It seems that to do this you need an idea of how to identify an individual amongst several screen shots using biometric data, and so this would require a biometric database to be constructed somewhere to tell you if the face is new, or a repeat visitor – not something we would really want to explore given the sensitive nature of this data.

So this leaves us with data that does not resolve to the unique number of people in a space over time, but the number of people in a single moment, which when plotted over time is something like an average – and so our dashboard would feature  “the average emotional state over time” or “the average gender”. As the same individual could be snapped in different emotional states. 

As ever with analytical systems the learning point here is to decide exactly on what to measure and how to analyse the data before choosing the technology – which is why hackathons are so great because the end product is not business critical and our prototype has given us some food for thought.

With GDPR presenting a barrier for experimenting with the Face API, I wonder whether we might have some fun pointing it at our museum collections to analyse the emotional states of the subjects of our paintings instead?

Acknowledgements:

Thanks to Zengenti for creating / hosting the event: https://www.zengenti.com/en-gb/blog

References:

Git repo for the project: https://github.com/blackradley/coeus

https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/781745/Facial_Recognition_Briefing_BFEG_February_2019.pdf
https://iapp.org/news/a/how-should-we-regulate-facial-recognition-technology/
https://thenextweb.com/contributors/2018/10/29/heres-how-face-recognition-tech-can-be-gdpr-compliant/
https://ico.org.uk/for-organisations/in-your-sector/business/general-data-protection-regulation-gdpr-faqs-for-small-retailers/

M Shed shop refit ChangeLog 2019

We’ll be writing a short update each day about how M Shed shop refit is progressing. Ahead of the refit the wider team used Basecamp to discuss the new shop design and for all decision approval. Lots of time has been spent recently on the finer details including bay depth, lighting of bays, till location and opportunities for adding value in the design. Let’s go!

Pssst you can read about our last refit changelog at Bristol Museum & Art Gallery in 2018 which has since sales increase 51% in 12months

Friday 5th July

Day 5 – voilà

install Trim, slat, glass doors, locks, first lit bay, clean, merchandise…open 16:30 and took our first sale (#236160 for £29.44 to tourists).

Thursday 4th July

Photo showing how the shop looks at the end of day 4 with glass in bays and power to the till
End of day 4 showing bays with glass shelving, power to the till and only minor work remaining

At the beginning of the day I was quietly confidently telling folks we’ll be done by end of Friday. Not 100% all singing and dancing and not a minimum viable product (MVP) but “good enough” to trade. Im not sure anyone believed me though (chuckles) as on the surface it did look far off. However much of that was due to the tools/cutting areas giving the impression of being far off.

Our electrician did a stellar job of getting power running to the till area and completing the wiring of the bay lighting and TVs. The bay lighting isn’t hooked up yet but this will be completed early next week and doesn’t pose an issue to trade over the weekend.

The shop fitters completed the final bays and slat wall. At the same time a few helpful hands (THANKS!) added the glass shelving. We only had a few book shelves on-site but ARJ-CRE8 super kindly have arranged for the rest to be delivered on Day 5. We started to pack down the temporary pop-up shop and transfer products to their new homes. By the end of the day we were all tidying up ready for a deep clean tomorrow morning. I was even reunited with my favourite tool, the pallet truck (long standing joke!) which we put to good use – a pallet truck is the workhorse of moving “stuff” with ease.

Helen and I will make a call about re-opening the shop tomorrow (end of the day) but I can’t see why we won’t be in that position by lunchtime… last big push which is mainly going to be getting product out.

Thanks to everyone who has been giving words of support, lending a hand or making jokes!

See you at 7am to help us move products right?

Wednesday 3rd July

Day 3 was very productive!

The shop fitters were able to complete the perimeter bays as shown below. Above the bays we’ve decided to make frames to hold graphics and tighten up the brand. I originally wanted to have digital screens but the cost didn’t outweigh the benefits and we can use some of our historic photos from around the harbour. Also the team didn’t like my idea which is fine!

Day 3 showing the shop with all perimeter bays in place and the till point area.
Day 3 photo showing the shop with all perimeter bays in place and the till point area.

In addition to some more decoration our brilliant in-house electrician had his first day on the project. He has the task of working out how best to power the LED bay lights, till area and our digital screens that will be behind the till. With the welcome news that the shop fitters expect to be finished early, our timeline has moved up. I asked Rob to focus first on powering our till as I have my fingers crossed we can then trade Friday. Once the till (shown below) has power we “can” be in business. After the till lighting the bays is the second priority then finally our digital screens.

Photo of our new till area.
Our new till area is now in place – woot!
Photo of a giant hole in the ground…well that was unexpected…

In the above photo there is a giant hole in the floor! This was under a bit of wall we removed and that needs to be “made good” so thankfully our ever awesome operations team arranged for a steel plug to be made today to save the day. Snags are always going to crop up and having professionals all around you makes them disappear pretty quickly. The hole needed to be filled as 1/2 of a bay unit was due to be installed at that spot.. thanks everyone who kicked into action to resolve today.

Our graphics have also gone to the printers today and will be installed Monday. In a project like this I’d much rather add new elements one by one rather than have tried to push too hard for all elements and contractors to work around each other. Having the project be ahead gives even greater buffer. Onwards!

Tuesday 2nd July

Day 2 has been rapid and already has enough done to see it coming together in real life as opposed to doodles and words! One set of contractors set about decorating and also building a new room to support our back of house function for the museum. Our design team chose the colour scheme which is designed to reinforce the brand and make the products shine.

Photo showing progress from day 2 which includes decorating and installing window bays
Day 2 progress which included wall bays and decorating. Photo by ARJ-CRE8

The shop fitters concentrated their efforts on installing the window bays and even found time to begin on the far back wall. More fittings arrived too such as glass shelving, our new custom marble table and other book tables. We expect each table to generate £5,000+ in annual sales.

We made a design decision to install bays directly in front of our windows across most of the space instead of retaining a “view” from the outside into the shop. We initially wanted to retain the “view” into the shop or use beautiful visual merchandised displays. However the displays required too much space which would reduce our shop floor area by 1m+. And keeping windows would eliminate our ability to increase overall “shoppable” space which is the aim of the game. We also took advice from a professional Visual merchandiser and between us the recommendation was “bays over beauty”. If it doesn’t add valuable then don’t do it. In the end a sensible comprise for budget reasons and to still retain some natural light at eye level was to have bays on the sides and keep the central of the windows open.

The decision to put bays in the window produced a new opportunity for us. We are now able to place graphics on the windows to promote our shop offer. Originally we planned to apply the graphics to the inside of the windows but missed the window of opportunity (bad joke) so instead will apply to the outside of the windows. This is actually a blessing in disguise as it now means we can change the graphics more frequently without a lengthy process of having to remove the bays to work. Below is the draft design we will send to the printers this week. You’ll see that two windows are to remain free and “viewable” from the outside. Natural light will still come in from the top panes.

Photo showing what the draft graphic will look like on the outer window - a giant M from our style guide
Photo showing what the draft graphic will look like on the outer window – a giant M from our style guide

In the windows that are in the foyer area there is the opportunity to expand beyond promoting retail to help explain what M Shed is and what we have on offer. Tomorrow i’ll ask our designer Fi what is possible in the four bays shown below.

The photo shows four windows that now show the back of the retail bays so we need to apply graphics to the outside windows.
The photo shows four windows that now show the back of the retail bays so we need to apply graphics to the outside windows.

Monday 1st July

ARJ-CRE8 arrived on site at 07:00 and were greeted by our Retail Manager Helen. Today’s schedule was to focus on the stripe out the current old shop fittings. The photo below shows a bare shop within just a few hours. Claudia and Helen spent the day helping where possible and getting our temporary pop-up shop ready.

 Photo of striped out M Shed shop

Once the old shop was stripped out the team then brought in lots of the new shop bays and fittings. At the same time, anther company were moving various sensors and alarms as we need to re-site lots of “bits” that were built into the original reception area. Fi, our 2D designer was also finalising graphics for the walls and windows. Onwards!

Photo showing the new shop fittings neatly laid out ready for the installation.
Photo showing the new shop fitting neatly stacked for install
Floor plan birds eye view showing a 2D pln of each part of the shop including all bays.
The floor plan of what the shop and reception areas will look like

Sunday 30th June

The last day of the current shop as we know it. Once the shop closed at 5pm a number of the team packed away all products on display. Products were either moved to the temporary “pop-up” shop area in the foyer or moved upstairs to our meeting room which is acting as our transit space during the project. At 07:00 the shopfitters from ARJ-CRE8 will be on-site to begin the project proper. Let’s hope the skip arrives earlier at day 1 is largely taking out the existing shop fittings and fixtures.

Can neural networks help us reinterpret history?

Background

Bristol City Council publishes many types of raw data to be transparent about the information they hold, and to encourage positive projects based on this data by any citizen or organisation.

One of the most recent datasets to be published by Bristol Museums is thousands of images from the British Empire and Commonwealth (BEC) collection. You can see a curated selection of these images online “Empire through the Lens.

At a hackathon hosted by Bristol’s Open Data team with support from the Jean Golding Institute, attendees were encouraged to make use of this new dataset. Our team formed around an idea of using image style transfer, a process of transforming the artistic style of one image based on another using Convolutional Neural Networks.

In layman’s terms this method breaks down images into ‘content’ components and ‘style’ components, then combines them.

We hypothesised there would be value in restyling images from the dataset to draw out themes of Bristol’s economic and cultural history when it comes to Empire and Commonwealth.

The team

  • Dave Rowe – Development Technical Lead for Bristol City Council and Open Data enthusiast
  • Junfan Huang – MSc Mathematics of Cybersecurity student in University of Bristol
  • Mark Pajak – Head of Digital at Bristol City Council Culture Team & Bristol Museums
  • Rob Griffiths – Bristol resident and Artificial Intelligence Consultant for BJSS in the South West

Aim

To assess the potential of Style Transfer as a technique for bringing attention back to historical images and exploring aspects of their modern relevance.

Method

Natalie Thurlby from the Jean Golding Institute introduced us to a method of style transfer using Lucid, a set of open source tools for working with neural networks. You can view the full Colab notebook we used here.

To start with, we hand-selected images from the collection we thought it would be interesting to transform. We tried to pair each ‘content’ image with ‘style’ images that might draw parallels with Bristol.

Dockside Cranes


A railway steam crane lowers a train engine onto a bogie on the dockside at Kilindini harbour, Mombasa, Kenya.

When we saw this image it immediately made us think of the docks at Bristol harbourside, by the Mshed.

The SS Harmonides which transported the train [likely from Liverpool actually] to Kenya is just visible, docked further along the harbour.

In addition to the images, the data set has keywords and descriptions which provide a useful way to search and filter

[‘railway’, ‘steam’, ‘crane’, ‘lower’, ‘train’, ‘engine’, ‘bogie’, ‘dockside’, ‘Kilindini’, ‘harbour’, ‘Mombasa’, ‘Kenya’]


We liked this painting by Mark Buck called the Cranes of Bristol Harbour. It says online that Mark studied for a degree in illustration at Bower Ashton Art College in Bristol, not too far from this place.

This image has been created as a result of adding the previous two images into the style tranfer engine.


We drew an obvious parallel here between these two sets of cranes in ports around the world. The Bristol cranes are from the 1950s, but the Kenya photo was taken much earlier, in the 1920s It would be interesting to look more deeply at the cargo flows between these two ports during the 19th century.

Cliftonwood Palace


This is a view of the Victoria Memorial, Kolkata, India in 1921.

It was commissioned by Lord Curzon to commemorate the death of Queen Victoria.

We were struck by the grandeur and formality of the photo.

Key words: [‘Victoria’, ‘Memorial’, ‘Kolkata’, ‘India’, ‘1921’] – see “topic modelling below”


A photo of the colourful Victorian terraces of Cliftonwood from the river, which have their own sense of formality.

The architectural significance of these buildings in their locales and link to Queen Victoria are small parallels.

It’s funny how the system seemingly tries to reconstruct the grand building using these houses as colourful building blocks, but it ends up making it look like a shanty town.

This image was created by machine intelligence by taking an historical photograph and applying a style gleaned from a bristol cityscape.

Caribbean Carnival


Carnival dancers on Nevis, the island in the Caribbean Sea, in 1965.

Two men perform a carnival dance outdoors, accompanied by a musical band. Both dancers wear crowns adorned with peacock feathers and costumes made from ribbons and scarves.

Key words: [‘perform’, ‘carnival’, ‘dance’, ‘outdoors’, ‘accompany’, ‘musical’, ‘dancer’, ‘crown’, ‘adorn’, ‘peacock’, ‘feather’, ‘costume’, ‘ribbon’, ‘scarf’, ‘Nevis’]

St Pauls Carnival is an annual African-Caribbean carnival held, usually on the first Saturday of July, in St Pauls, Bristol.

We selected this picture to see how the system would handle the colourful feathers and sequined outfits.

The resulting image (below) was somewhat abstract but we agreed was transformed by the vibrant colours and patterns of movement.

Festival colours reimagine an historical photograph using machine intelligence – but is this a valid interpretation of the past or an abstract and meaningless picture?

After generating many examples we came together to discuss some of the ethical and legal implications of this technique.

We were particularly mindful of the fact that any discussion of Empire and Commonwealth should be treated with sensitivity. For each image, it’s challenging both to appreciate fully the context and not to project novelty or inappropriate meaning onto it.

We wondered whether this form of style transfer with heritage images was an interesting technique for people who have something to say and want an eye-catching way of communicating, but not a technique that should be used lightly – particularly with this dataset.

We often found ourselves coming back to discussions of media rights and intellectual property. None of us have a legal background but we were aware that, while we wanted to acknowledge where we had borrowed other people’s work to perform this experiment, we were generating new works of art – and it was unclear where the ownership lay.

Service Design

We set out potential benefits of our service:

  • A hosted online service to make it a more efficient process
  • Advice and tips on how to calibrate and get the best results from Style Transfer
  • Ability to process images in bulk
  • Interactive ways of browsing the dataset
  • Communication tools for publishing and sharing results
  • Interfaces for public engagement with the tool – a Twitter conversational bot

On the first day we started putting together ideas for how a web service might be used to take source images from the Open Data Platform and automate the style stransfer process.

This caused us to think about potential users of the system and what debate might be sparked fromt he resulting images.

Proposition Design

A key requirement for all users would be the ability to explore and see the photographs in their original digitised form, with the available descriptions and other metadata. Those particularly interested in exploring the underlying data would appreciate having search and filter facilities that made use of fields such as location, date, and descriptions.

We would also need a simple way of choosing a set of photographs, without getting in the way of being able to continue to discover other photos. A bit like in an online shopping scenario where you add items to a basket.

The users could then choose a style to apply to their chosen photos. This would be a selection of Bristol artworks, or iconic scenes. For those wanting to apply their own style (artists, for example) we would give an option to upload their own artwork and images.

Depending on processing power, we know that such an online service could have difficulty applying style transforms in an appropriate time for people to wait. If the waiting time were over a couple of minutes it could be that the results are provided by email.

Components

Spin off products…Topic Modelling

We even successfully built a crucial component of our future service. The metadata surrounding the images includes both keywords and descriptive text. Junfan developed a script that analysed the metadata to provide a better understanding of the range of keywords that could be used to interrogate the images. This could potentially be used in the application to enable browsing by subject….

We wanted to generate a list of keywords from the long form text captions that accompanied the images. This would allow us to come up with a classification for pictures using their description. Then, users would be able to select topics and get some pictures they want.

Here in topic 2, our model has added bridge, street, river, house, gardens and some similar words into the same group.

Python is the language of choice for this particular application
Topic modelling reveals patterns of keyword abundance amongst the captions
keywords extracted from the captions can help us build an interface to allow filtering on a theme

Reflections

After generating many examples we came together to discuss some of the ethical and legal implications of this technique.

We were particularly mindful of the fact that any discussion of Empire and Commonwealth should be treated with sensitivity. For each image, it’s challenging both to appreciate fully the context and not to project novelty or inappropriate meaning onto it.

We wondered whether this form of style transfer with heritage images was an interesting technique for people who have something to say and want an eye-catching way of communicating, but not a technique that should be used lightly – particularly with this dataset.

We often found ourselves coming back to discussions of media rights and intellectual property. None of us have a legal background but we were aware that, while we wanted to acknowledge where we had borrowed other people’s work to perform this experiment, we were generating new works of art – and it was unclear where the ownership lay.

Does this have potential?

We thought, on balance, yes this was an interesting technique for both artistic historians and artists interested in history.

We imagined their needs using the following user personas:

  • Artistic Historians: ‘I want to explore the stories behind these images and bring them to life in a contemporary way for my audience.’
  • Artists interested in history: ‘I want a creative tool to provide inspiration and see what my own personal, artistic style would look like applied to heritage images’.

We spent time scoping ways we could turn our work so far into a service to support these user groups.

References & Links

  • The repo for our application: https://github.com/xihajun/Art-vs-History-Open-Data-Hackathon-Code
  • Open data platform:https://opendata.bristol.gov.uk/pages/homepage/
  • Bristol Archives (British Empire and Commonwealth Collection): https://www.bristolmuseums.org.uk/bristol-archives/whats-at/our-collections/

Acknowledgements

Thanks to Bristol Open for co-ordinating the Hackathon.

Thanks to Lucid contributors for developing the Style Transfer code.

Thanks to the following artists for source artwork:

Mark Buck: https://www.painters-online.co.uk/artist/markbuck

Ellie Pajak

https://www.etsy.com/shop/PapierBeau?section_id=21122286

Open Data

Hi, my name is Hannah Boast and I am an apprentice working in the City Innovation Team for Bristol City Council. Our aim as a team is to create a smarter digital future for Bristol. A wide range of projects are currently being worked on by the City Innovation team such as driverless cars, smart homes and ultrafast broadband. A project I would like to elaborate on which our team is also involved in is maintaining and promoting the Open Data platform.

Bristol’s open data platform’s objective is to have accessible data that is widely available to the public and to organisations. By increasing data transparency it can open opportunities for discovering new insights of the city and support our digital economy. Successfully we have recently been co-ordinating data hackathons and data jams which involve gathering people who collaboratively code over a short period of time. During this attendees will be working on a particular project and the idea is for the teams to have the ability and freedom to work on whatever he/she wants. These engagements run along with contributing partners such as organisations and the data community. The data engagements can help us understand the aims of the interested public in open data and bringing in a new generation of people who can help drive and contribute to open data in Bristol. Keep up to date on any upcoming events on our Connecting Bristol website.

Bristol Museum & Art gallery are currently digitalising their collection of artefacts to make it accessible to a wide range of people online. A great  example is The Natural History Museum data portal it has uploaded a great deal of the museums artefacts. This gives the public access to find out more detailed information on what is held at the museum.

Get in contact with us to find out more on open data in Bristol: opendata@bristol.gov.uk

Testing museum gallery mobile interpretation

smartify logo

Over the next few weeks we are running user testing of SMARTIFY at M Shed. This app provides visitors with extra information about museum objects using image recognition to trigger the content on a mobile device.

To install the free app use this link: https://smartify.org/

If you have used the app at M Shed, please could you take a few moments to complete the following survey: https://www.surveymonkey.co.uk/r/ZVTVPW9

If you would like to help further, please get in touch with our volunteer co-ordinator: https://www.bristolmuseums.org.uk/jobs-volunteering/

 

Sharing our retail performance

May I introduce the Retail Performance dashboard. Since taking on retail in 2015 we’re proud to have increased sales by 60% in three years. We’ve gone from loss making to profitable  and at the time of writings we are up 22% compared to last year. What that really means is that our retail efforts will contribute £100,000+ profit back to the service which keeps 2 or 3 staff outside of retail in employment. I jokingly say that our sales of ‘fart whistles’ are literally keeping others in gainful employment!

I regularly tweet stats of our retail performance so thought i’d now take that up a notch and share a dashboard that you can use to see the data yourself. The digital team are working on some much slicker visualisations but for now this will do.

The Retail Performance dashboard, powered by Google Data Studio .

Things to add include:

How to nail it in Team Digital by turning it off.

This post is about my recent week of reducing screen time to a minimum after seeking a fresh approach, having lost the plot deep in some troublesome code, overloaded with an email avalanche and pestered by projects going stale. In other words…have you tried turning it off? (and not on again!)

STEP 1: TURN OFF PC

Guys this is what a computer looks like when it is off

Kinda feels better already. No more spinning cogs, no more broken code, brain starting to think in more creative ways, generally mind feeling lighter.  Trip to the stationary cupboard to stock up on Post-its and sticky things, on way speak to a colleague whom I wouldn’t usually encounter and gain an insight into the user facing end of a project I am currently working on (I try to make a mental note of that).

STEP 2: RECAP ON AGILE METHODS

Agile Service Delivery concept
a great diagram about agile processes by Jamie Arnold

(admittedly you do need to turn the computer back on from here onwards, but you get the idea!)

The team here have just completed SCRUM training and we are tasked with scratching our heads over how to translate this to our own working practices. I was particularly inspired by this diagram and blog by Jamie Arnold from G.D.S.  explaining how to run projects in an agile way. I am especially prone to wanting to see things in diagrams, and this tends to be suppressed by too much screen time 🙁

“a picture paints a thousand words.”

Also for projects that are stalled or for whatever reason on the backburner – a recap (or even retrospective creation) on the vision and goals can help you remember why they were once on the agenda in the first place, or if they still should be.

STEP 3: FOCUS ON USER NEEDS

It is actually much easier to concentrate on user needs with the computers switched off. Particularly in the museum where immediately outside the office are a tonne of visitors getting on with their lives, interacting with our products and services, for better or worse.  Since several of our projects involve large scale transformation of museum technology, mapping out how the user need is acheived from the range of possible technologies is useful. This post on mapping out the value chain explaines one method.

Mapping the value chain for donation technology

Whilst the resulting spider-web can be intimidating, it certainly helped identify some key dependencies like power and wifi (often overlooked in musuem projects but then causing serious headaches down the line) as well as where extra resource would be needed in developing new services and designs that don’t yet come ‘off the shelf’.

STEP 4: DISCOVERING PRODUCT DISCOVERY

There is almost always one, or more like three of our projects in the discovery phase at any one time, and this video form Teresa Torres on product discovery explains how to take the focus away from features and think more about outcomes, but also how to join the two in a methodical way – testing many solutions at once to analyse different ways of doing things.

We are a small multidisciplinary team, and in that I mean we each need to take on several disciplines at once, from user research, data analysis, coding, system admin, content editing, online shop order fulfilment (yes you heard that right) etc. However, it is always interesting to hear from those who can concentrate on a single line of work. With resources stretched we can waste time going down the wrong route, but we can and do collaborate with others to experiment on new solutions. Our ongoing “student as producer” projects with the University of Bristol have been a great way for us to get insights in this way at low risk whilst helping to upskill a new generation.

STEP 5: GAMIFY THE PROBLEM

Some of the hardest problems are those involving potential conflict between internal teams. These are easier to ignore than fix and therefore won’t get fixed by business as usual, they just linger and manifest, continuing to cause frustration.

Matt Locke explained it elegantly in MCG’s Museums+Tech 2018: the collaborative museum. And this got me thinking about how to attempt to align project teams that run on totally different rhythms and technologies. Last week I probably would have tried to build something in Excel or web-based tech that visualised resources over time, but no, not this week….this week I decided to use ducks!

Shooting ducks on a pinboard turned out to be a much easier way to negotiate resources and was quicker to prototype than any amount of coffee and coding (its also much easier to support 😉 ). It was also clear that Google sheets or project charts weren’t going to cut it for this particular combination of teams because each had its own way of doing things.

The challenge was to see how many weeks in a year would be available after a team had been booked for known projects. The gap analysis can be done at a glance – we can now discuss the blocks of free time for potential projects and barter for ducks, which is more fun than email crossfire. The problem has now become a physical puzzle where the negative space (illustrated by red dots)  is much more apparent than it was by cross-referencing data squares vs calendars. Its also taken out the underlying agendas across departments and helped us all focus on the problem by playing the same game – helping to synchronise our internal rhythms.

REMARKS

It may have come as a surprise for colleagues to see their digital people switch off and reach for analogue tools, kick back with a pen and paper and start sketching or shooting ducks, but to be honest its been one of the most productive weeks in recent times, and we have new ideas about old problems.

Yes, many bugs still linger in the code, but rather than hunting every last one to extinction, with the benefit of a wider awareness of the needs of our users and teams, maybe we just switch things off and concentrate on building what people actually want?

 

 

 

 

 

Digital interpretation in our galleries: Discovery kick-off

Our temporary exhibitions have around a 20% conversion rate on average. While we feel this is good (temporary exhibitions are either paid entry or ‘pay what you think’, bringing in much-needed income), flip that around and it means that around 80% of people are visiting what we call our ‘permanent galleries’ – spaces that change much less often than exhibitions. With a million visitors every year across all of our sites (but concentrated at M Shed and Bristol Museum & Art Gallery), that’s a lot of people.

A lot of our time as a digital team is taken up with temporary exhibitions at M Shed and Bristol Museum. Especially so for Zahid, our Content Designer, who looks after all of our AV and whose time is taken up with installs, derigs and AV support.

But what about all of the digital interpretation in our permanent galleries? Focusing on the two main museums mentioned above, we’ve got a wide range of interp such as info screens, QR codes triggering content, audio guides and kiosks. A lot of this is legacy stuff which we don’t actively update, either in terms of content or software/hardware. Other bits are newer – things we’ve been testing out or one-off installs.

So, how do we know what’s working? How do we know what we should be replacing digital interp with when it’s come to the end of its life – *IF* we should replace it at all? How do we know where we should focus our limited time (and money) for optimal visitor experience?

We’ve just started some discovery phases to collate all of our evidence and to gather more. We want a bigger picture of what’s successful and what isn’t. We need to be clear on how we can be as accessible as possible. We want to know what tech is worth investing in (in terms of money and time) and what isn’t. This is an important phase of work for us which will inform how we do digital interpretation in the future – backed up by user research.

Discovery phases

We’ve set out a number of six week stints from August 2018 to January 2019 to gather data, starting with an audit of what we have, analytics and what evidence or data we collect.

We’ll then move onto looking at specific galleries– the Egypt Gallery at Bristol Museum and most of the galleries at M Shed which have a lot of kiosks with legacy content.  (The M Shed kiosks probably need a separate post in themselves. They were installed for when the museum opened in 2011, and since then technology and user behaviours have changed drastically. There’s a lot we could reflect on around design intentions vs reality vs content…)

We’ll also be gathering evidence on any audio content across all of our sites, looking at using our exhibitions online as interp within galleries and working on the Smartify app as part of the 5G testing at M Shed.

We’re using this trello board to manage the project, if you want to follow what we’re doing.

Auditing our digital interpretation

First off, we simply needed to know what we have in the galleries. Our apprentice Rowan kindly went around and scoured the galleries, listing every single thing she could find – from QR codes to interactive games.

We then categorised everything, coming up with the below categories. This has really helped to give an overview of what we’re working with.

Key Level of interaction Examples User control
1 Passive Auto play / looping video, static digital label, info screens User has no control
2 Initiate QR code / URL to extra content, audio guide User triggers content, mostly on own or separate device
3 Active Games and puzzles, timeline User has complete control. Device in gallery

We then went through and listed what analytics we currently gather for each item or what action we need to take to set them up. Some things, such as info screens are ‘passive’ so we wouldn’t gather usage data for. Other things such as games built with Flash and DiscoveryPENs (accessible devices for audio tours), don’t have in-built analytics so we’ll need to ask our front of house teams to gather evidence and feedback from users. We’ll also be doing a load of observations in the galleries.

Now that people have devices in their pockets more powerful than a lot of the legacy digital interpretation in our galleries, should we be moving towards a focus on creating content for use on ‘BYO devices’ instead of installing tech on-site which will inevitably be out of date in a few short years? Is this a more accessible way of doing digital interpretation?

Let us know what you think or if you have any evidence you’re happy to share with us. I’d be really interested to hear back from museums (or any visitor attractions really) of varying sizes. We’ll keep you updated with what we find out.

Fay Curtis – User Researcher

Zahid Jaffer – Content Designer

Mark Pajak – Head of Digital

My Digital Apprenticeship with Bristol Culture

Hi! My name is Cameron Hill and I am currently working as a Digital Apprentice as part of 

Cameron Hill

the Bristol City Council Culture Team, where I’ll mainly be based at Bristol Museum and helping out with all things digital.

Previously to joining Bristol City Council, I studied Creative Media at SGS College for two years as well as at school for GCSE. A huge interest of mine is social media. Whilst at college I worked with a friend who was a fashion student who sold her creations to create more of a brand for herself. After she came up with the name, I created an Instagram page for the brand and started creating various types of content. Using Instagram stories was a great way to interact with followers. Using different features such as Q&A and polls, it was easy to see what the customers like. Something else we did with stories was showing the ‘behind the scenes’. For example: from picking the fabric, making the item itself and packing the item to be shipped.

As I am writing this it is my first day and so far it has been a lot to take in. One of my first tasks was to upload an image to a folder linked to the various screens around the museum. 

Digital signage not working

Although technology can be temperamental, the first issue we came across was unexpected….

Using my iPhone, I was asked to take an image to upload into the folder but without me realising the phone camera had ‘live photos’ turned on meaning all pictures taken would create small video clips.  After waiting for five minutes or so and the image not appearing we realised that the image was taken in High-Efficiency Image File Format (HEIC). Not knowing what HEIC was I did what anyone in the twenty-first century would do and took to Google.

 

After a little research, I came across an article in a technology magazine, The Verge stating that this format that Apple has added to iOS 11 would be a problem for PC users. From reading various articles online it is clear that a lot of people have struggled 

when trying to upload their files to PCs and not being able to view and edit it. I am really looking forward to my future working here as part of the Digital Team.